Date of Degree
Social Capital, Analyst Forecasts
This study examines the effect of social capital on analyst forecast accuracy. Using a county-level measure of social capital, I find that firms headquartered in counties with high social capital have greater forecast accuracy than firms headquartered in low social capital counties. In addition, I conduct two cross-sectional tests under conditions where social capital facilitates analyst forecast information collection and where social capital provides more assurance of information reliability. I find that the effect of social capital is more pronounced when firms’ headquarters are close to analyst brokerage firms. This is because geographically proximate analysts may have more channels to collect information. I also show that since high social capital can reduce analysts’ time and effort to verify the reported earnings when a firm has complicated operation, effect of social capital is more pronounced when a firm’s operation is complex. I also find that investors react more strongly to analyst forecast for firms headquartered in counties with low social capital, suggesting that the analyst’s role as an information intermediary is more valuable in this setting. Additionally, I employ the relocation of firms headquarters to better establish causality. The results are robust to regional fixed effect, accounting quality, management guidance, analyst fixed effect, and alternative measure of social capital. In sum, these findings suggest that social capital is an important factor that affects analysts forecast accuracy and informativenesss.
Dai, Jing, "Social Capital and Analyst Forecasts" (2018). CUNY Academic Works.
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